In transportation systems, the issue of ensuring driving safety and driver assistance is an important requirement. One of the factors which are responsible for the road accidents is either driver's ignorance or reduced range of vision. Conventional safety features like seat belts, airbags, Anti-lock braking system (ABS) are available for reducing severity of the accidents. Further, other safety features available today include driver-assistance systems helping the driver to avoid accidents by providing early alerts to the driver and if required taking over the control of a vehicle from the driver.
One of such driver-assistance systems may include collision avoidance system enabled for detecting objects in the path of the vehicle and alerting the driver. For detecting the objects, images may be captured and further processed for detecting an actual position of the objects from the vehicle. However, present techniques available for providing the collision avoidance system are capable of detecting the objects, one at a time, either placed at a far range or at a near range from the vehicle. Thus, the present driver-collision avoidance system face technical challenge of detecting the objects placed at the far range and the near range from the vehicle simultaneously. Additionally, the computation of objects, by the existing systems, at different ranges (far and near) requires more computational time which may further lead in delaying the response provided in form of notification alerts to the driver.